code: def get_selected_model_identifiers(
      self,
  ) -> List[Tuple[int, int, float]]:
      output = []
  
      for i, weight in enumerate(self.weights_):
          identifier = self.identifiers_[i]
          if weight > 0.0:
              output.append(identifier)
  
      return output
  
imports: from __future__ import annotations
  from typing import Dict, List, Sequence, Tuple, Union
  import random
  import warnings
  from collections import Counter
  import numpy
  from sklearn.utils import check_random_state
  from autosklearn.automl_common.common.utils.backend import Backend
  from autosklearn.constants import TASK_TYPES
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES
  from autosklearn.ensemble_building.run import Run
  from autosklearn.ensembles.abstract_ensemble import AbstractEnsemble
  from autosklearn.metrics import Scorer, calculate_losses
  from autosklearn.pipeline.base import BasePipeline
label_desc: Use image node_id 12 for calling the EnsembleSelection obj's underlying member method code with example usage: obj.get_selected_model_identifiers() and returns: output